Phase locked loops (PLLs) are employed to derive a precision output signal by locking on to an input reference signal. However, before the reference signal can be applied to a PLL, it is oftentimes first necessary to determine whether the reference signal meets certain stability criteria, both as to jitter and wander. Jitter refers to short-term phase variations in the signal, whereas wander refers to gradual phase shifts occurring over longer periods. The process of determining whether a reference signal meets the stability criteria is known as precision frequency monitoring (PFM). A reference signal is consider qualified if it meets the stability criteria and disqualified if it does not. These decisions have to be made with a high degree of accuracy because it is important not to allow a PLL to lock on to an unstable or incorrect clock frequency, for example, resulting from drift of a crystal oscillator.
A typical implementation is shown in FIG. 1. The reference clock (Clock in) is applied to a signal period estimation module 10, which provides an estimate of the signal period to a short-term averaging module 12. The short-term averaging module 12 obtains an average of the provided estimated period over a time period, T, which in typical embodiment is one second. The short-term averaging module 12 thus provides one output sample representing the estimated period every second. The resulting average Tx is passed through the low pass filter 14 to provide the PFM output signal. It will be appreciated that in an alternative embodiment the short-term averaging module may obtain an average of the frequency from the provided estimated period.
The PFM output signal is then compared with the desired period, or frequency, to determine whether the difference between the PFM output signal and the desired period, or frequency, lies within a predetermined qualification range. If yes, the signal is qualified; otherwise it is disqualified.
The design of the low pass filter 14 is an important consideration. To obtain an accurate measurement, a narrow band low pass filter is required to remove jitter. In the prior art a finite impulse response (FIR) filter whose register is periodically refreshed is employed because a FIR filter can rapidly respond to an input frequency change. An infinite impulse response (IIR) filter, while simpler to implement, is too slow to react to input frequency changes to offer high precision PFM.
The FIR filter is however the main bottleneck in a high precision PFM. A typical N-tap FIR filter is shown in FIG. 2. This comprises a chain of N unit delay registers, which are added together with equal weights. If a high precision long-term average is required, a large number of unit delay registers are required. For an N-tap FIR filter, the memory flush time is constant (N seconds) because a sample arrives every second and it thus takes N seconds for a data sample to pass through the filter. The memory flush time determines the amount of time that it takes for all the samples which contribute to the output to reflect the changed input. This arrangement guarantees a PFM value will be available N seconds after start-up. The PFM value will then be updated every second. However, such a FIR filter can be too complex and expensive to implement. Also, the performance of the FIR filter is limited by the number of taps N. Its frequency estimation accuracy increases from 0 to N seconds as the memory fills up upon the arrival of successive samples after start-up and then can never be improved, since after N seconds all the samples in memory reflect the changed input.